The practice of scientific research requires that beliefs and intuitions be verified against accepted knowledge. Investigators delving into the details of gene functions or of signal transmission in neurons constantly test their hypotheses against multiple knowledge resources. The methodology presented in this patent application proposes the automation of this process of hypothesis verification with respect to ontologies and knowledge resources. It provides mechanisms to encode beliefs and to verify them against ontology ecosystems created through the alignment of multiple ontologies. Verification of these hypotheses results in sets of ontology axioms that either corroborate or contradict them.
Recent years have seen a considerable expansion in the development of ontologies, due to their success in structuring knowledge for many different applications. Ontologies have proven their utility and potential in the annotation of data in support of research. The roles of ontologies can be classified into three major categories: knowledge management, including the indexing and retrieval of data and information; data integration, exchange and semantic interoperability; and decision support and reasoning.
Ontologies take advantage of Description Logics (DL)-based formalisms to represent knowledge. DL provide a strong mathematical underpinning for ontologies conceptualized in this way, where expressivity of ontologies is defined based upon the types of axioms allowed. DL also define reasoning or inferencing capabilities over ontologies, whereby axioms not explicitly asserted can be inferred based on logical consequences. The basic reasoning mechanisms afforded by ontologies are classification, or the ability to determine relationships between classes, and instance checking, or the ability to determine membership of an individual in a given class. The OWL 2 Web Ontology Language has expressivity of SROIQ(D), and it has been shown to be decidable in terms of reasoning. OWL 2, a principal component of the Semantic Web, is used to formalize a domain, assert properties about individuals, and reason about classes and individuals.
The recent growth of related but independently developed ontologies in multiple domains has both enabled and fragmented the field making it difficult to realize the full potential of ontologies. In biomedical research for example, despite a reasonable overlap in terms and concepts, different ontologies intersect little in their relations suggesting that each ontology covers only a small subset of the full range of possible human disease concepts and circumstances.